SKILLEMALL.ai
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AC aaes

This skill provides script-based email operations for an agent. It includes functionalities for managing mailboxes, reading/searching emails, sending/replying/forwarding emails, and managing attachments, allowing agents to perform comprehensive email-related tasks programmatically.

ClawHub Agent Skills author: Tyxiang v1.0.6 MIT-0 25 files body ≈ 4 410 tokens Open the sourceclawhub.ai↗ analyzed 5 d ago

As a process C 50/100 · Has gaps — weak spots: result and completion, when it triggers, consistency

ReferenceAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
98
Quality 40%
87
Run on models
none yet
Process rating
C
50/100
Has gaps
Result and completion w 14
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 2

    ✓ No critical or high findings

    Medium and low: 2
    • low Secrets in code secret-password-literal scripts/common/imap_utils.py:55
      Hard-coded password / key literal (may be an example)
      access_token = get_…ken(oauth_cfg)
    • low Secrets in code secret-password-literal scripts/common/smtp_utils.py:54
      Hard-coded password / key literal (may be an example)
      access_token = get_…ken(oauth_cfg)

    Files scanned: 25. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 50/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 24 mutating operations with no state check
    • 40Consistency. Frontmatter name (aaes) differs from the folder (ai-agent-email-skill)
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (web, python) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 70Execution cost. Instruction body is 4410 tokens
    • 100Steps. 33 steps
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +3Description length 282: enough signal without eating the budget
    • +4Structure: 41 headings
    • +3Step-by-step instructions: 33 items
    • +4Has examples (12 code blocks)
    • +3All 13 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.

    External checks

    ClawHub: clean
    This is a high-authority email automation skill, but its mailbox access, sending, forwarding, and deletion capabilities are disclosed and match its stated purpose.
    LLM: benign (high) · VirusTotal: · 29 May 2026